论文标题
基于秘密密钥的身份验证，带被动性窃听标量高斯来源
Secret Key-based Authentication With Passive Eavesdropper for Scalar Gaussian Sources
论文作者
论文摘要
我们分析了在窃听的高斯来源的窃听器的存在下，分析了基于密钥的身份验证系统的基本权衡。提供了生成和所选秘密模型的秘密，存储和隐私透明率之间的权衡表征。主要贡献之一是揭示了与离散来源的已知结果不同，在表征高斯病例的容量区域时，不需要第二个辅助随机变量。此外，还表明，可以通过信息光谱方法来实现系统的保密性秘密，并且还得出了容量区域的参数表达式（可计算形式）。
We analyze the fundamental trade-off of secret key-based authentication systems in the presence of an eavesdropper for correlated Gaussian sources. A complete characterization of trade-off among secret-key, storage, and privacy-leakage rates of both generated and chosen secret models is provided. One of the main contributions is revealing that unlike the known results for discrete sources, there is no need for the second auxiliary random variable in characterizing the capacity regions for the Gaussian cases. In addition, it is shown that the strong secrecy for secrecy-leakage of the systems can be achieved by an information-spectrum approach, and the parametric expressions (computable forms) of the capacity regions are also derived.
